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AnyMo framework enables setup-agnostic human motion modeling

Researchers have developed AnyMo, a novel framework designed to overcome the setup-dependency challenges in modeling human motion from wearable inertial measurement units (IMUs). The system utilizes physics-grounded simulation to generate synthetic data, enabling a graph encoder to learn representations that are agnostic to sensor placement and device variations. AnyMo tokenizes multi-position IMU data and aligns it with a large language model for enhanced motion understanding, demonstrating significant improvements in zero-shot activity recognition, cross-modal retrieval, and motion captioning. AI

IMPACT Enables more robust and transferable human motion analysis from wearable sensors, potentially improving applications in healthcare, sports, and robotics.

RANK_REASON The cluster contains an academic paper detailing a new framework for human motion modeling.

Read on Hugging Face Daily Papers →

AI-generated summary · Google Gemini · from 3 sources. How we write summaries →

COVERAGE [3]

  1. arXiv cs.CL TIER_1 English(EN) · Baiyu Chen, Zechen Li, Wilson Wongso, Lihuan Li, Xiachong Lin, Hao Xue, Benjamin Tag, Flora Salim ·

    AnyMo: Geometry-Aware Setup-Agnostic Modeling of Human Motion in the Wild

    arXiv:2605.22715v1 Announce Type: cross Abstract: As wearable and mobile devices become increasingly embedded in daily life, they offer a practical way to continuously sense human motion in the wild. But inertial signals are highly dependent on the sensing setup, including body l…

  2. arXiv cs.AI TIER_1 English(EN) · Flora Salim ·

    AnyMo: Geometry-Aware Setup-Agnostic Modeling of Human Motion in the Wild

    As wearable and mobile devices become increasingly embedded in daily life, they offer a practical way to continuously sense human motion in the wild. But inertial signals are highly dependent on the sensing setup, including body location, mounting position, sensor orientation, de…

  3. Hugging Face Daily Papers TIER_1 English(EN) ·

    AnyMo: Geometry-Aware Setup-Agnostic Modeling of Human Motion in the Wild

    AnyMo is a geometry-aware framework that enables setup-agnostic human motion modeling using physics-grounded IMU simulation and graph encoding for cross-dataset activity recognition and cross-modal retrieval.